Revisiting the role of hypoxia-inducible factors and nuclear factor erythroid 2-related factor 2 in regulating macrophage inflammation and metabolism
Bibliographic record
Abstract
The recent birth of the immunometabolism field has comprehensively demonstrated how the rewiring of intracellular metabolism is critical for supporting the effector functions of many immune cell types, such as myeloid cells. Among all, the transcriptional regulation mediated by Hypoxia-Inducible Factors (HIFs) and Nuclear factor erythroid 2-related factor 2 (NRF2) have been consistently shown to play critical roles in regulating the glycolytic metabolism, redox homeostasis and inflammatory responses of macrophages (Mφs). Although both of these transcription factors were first discovered back in the 1990s, new advances in understanding their function and regulations have been continuously made in the context of immunometabolism. Therefore, this review attempts to summarize the traditionally and newly identified functions of these transcription factors, including their roles in orchestrating the key events that take place during glycolytic reprogramming in activated myeloid cells, as well as their roles in mediating Mφ inflammatory responses in various bacterial infection models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".